Computing the 3D position and 3D orientation of a camera with respect to a geometric representation of the scene (which is sometimes referred to as image-based localization) has important applications in location recognition, autonomous robot navigation, and augmented reality, among others. Broadly speaking, there are two approaches to image-based localization. The first involves simultaneous localization and mapping (SLAM), where the camera is localized within an unknown scene. In contrast, approaches in the second category use the knowledge of a prior map or 3D scene model.
It is believed the second approach has the most promise with regard real-time image-based localization in large environments. Such real-time, large environment image-based localization is needed for example in autonomous aerial navigation, especially in GPS-denied areas. It is particularly attractive for micro-aerial vehicles (MAV), such as a quadrotor, which can have limited payload but be capable of full-fledged onboard vision processing.